Generalized estimating equations for longitudinal mixed Rasch model

In this paper, the problem of estimating the fixed effects parameters and the variance of the random effects (variance components) in longitudinal mixed Rasch model is considered. It is well known that estimating these parameters by the method of maximum likelihood faces computational difficulties. As an alternative, we propose the generalized estimating equations approach. Approximations of the joint moments of the variables are proposed. The estimators obtained are consistent and asymptotically normal. We illustrate the usefulness of the method with simulations and with an analysis of real data from quality of life.